The Relationship Between Lower Respiratory Tract Microbiome and Allergic Respiratory Tract Diseases in Children

Abstract

Similar to those in the upper respiratory tract, there are microbes present in the healthy human lower respiratory tract (LRT), including the lungs and bronchus. To evaluate the relationship between LRT microbiome and allergic respiratory diseases in children, we enrolled 68 children who underwent bronchoscopy from January 2018 to December 2018 in the affiliated hospital of the Capital Institute of Pediatrics. Using the total IgE (TIgE) values, children were divided into two groups: allergy sensitivity (AS) group and non-allergy sensitivity (NAS) group. Nucleic acid was extracted from samples of bronchoalveolar lavage fluid (BALF) from the two groups of children taken during bronchoscopy treatment and the 16S rDNA gene was sequenced and analyzed. The results showed that Haemophilus, Moraxella, Streptococcus, Prevotella, Neisseria, and Rothia were detected in all patients. There was a statistically significant difference in the composition and distribution of microbiota between the AS and NAS groups (p < 0.01). Analysis of the correlation of clinical indices and microbiome showed that TIgE was positively correlated with Bacteroidetes and negatively correlated with Streptococcus. Absolute lymphocyte count showed a relationship with Streptococcus, and the absolute neutrophil count or percentage of neutrophils showed a relationship with Cardiobacterium. The LRT microbiome functioned similarly to the intestinal microbiome. That is, the decrease in microbial diversity and the change in composition could lead to an increase in allergic symptoms. The microbiome of the LRT in children, especially that of Bacteriodetes and Streptococcus, showed a correlation with respiratory allergic diseases.

Keywords: allergic respiratory tract diseases; bronchoalveolar lavage fluid; children; lower respiratory tract; microbiome.

FIGURE 1

The lower respiratory tract (LRT) microbiome composition profiles for the 68 patients in this study (A). The percentage of the six genera of bacteria was found in all patients (B).

FIGURE 2

A principal coordinate analysis (PCA) plot based on 16S rDNA sequencing of 64 lower respiratory tract (LRT) samples. The scatter plot shows principal coordinate 1 (PC1) vs. principal coordinate 2 (PC2). The percentages shown are percentages of variation explained by the components. The PCA profile of microbial diversity across all samples using the Bray–Curtis distance.

FIGURE 3

Streptococcus, Bacterodies, Lactobacillus, Anoxybacillus, Aerococcus, TG5, Pavimonas, and Cardiobacterium showed significant differences (p < 0.05) between the no allergy sensitivity (NAS) group and allergy sensitivity (AS) group (A). Color spots of the relative abundances of 30 species selected for the random forest (RF) model used to distinguish samples in no allergy sensitivity (NAS) group and allergy sensitivity (AS) group (B).

FIGURE 4

The alpha-diversity box and whisker plot of taxa richness in samples were analyzed by partial 16S rDNA sequencing. Index of Chao 1 (A), PD_whole_tree (B), Shannon (C), and Simpson (D) was calculated respectively.

FIGURE 5

The correlation heat map shows correlations between clinical indices and the relative abundance of genera. Correlation coefficients with the color value bar are shown in the blocks. NE%, LY%, and EO% present the percentage of neutrophile granulocyte, lymphocyte, and eosinophils count, respectively. NE#, LY#, and EO# present the absolute neutrophile granulocyte, lymphocyte, and eosinophils count, respectively. **P < 0.01, *P < 0.05.